The process of facial recognition is one of the most widely used video-analysis and image-analysis techniques employed today. In the public-safety context, a vast amount of visual data is obtained on a regular and indeed often substantially continuous basis. Oftentimes one would wish to identify, e.g., a person of interest in these images and recordings. It could be the case that the quick and accurate identification of said person of interest is of paramount importance to the safety of the public, whether in an airport, a train station, a high-traffic outdoor space, or some other location. Among other benefits, facial recognition can enable public-safety responders to identify persons of interest promptly and correctly. It is often the case, however, that the quality of the images being input to—and analyzed by—facial-recognition software is correlated with the accuracy and immediacy of the results. Poor image quality may be due to one or more of low resolution, indirect view of a person's face, less-than-ideal lighting conditions, and the like.
To reduce the negative impact of poor image quality, various pre-facial-recognition tools can be utilized. One category of such tools is known as super-resolution. Various super-resolution techniques exist. Accordingly, for this reason and others, there is a need for methods and systems for increasing facial-recognition working range through adaptive super-resolution.
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The apparatus and method components have been represented where appropriate by conventional symbols in the drawings, showing only those specific details that are pertinent to understanding the embodiments of the present invention so as not to obscure the disclosure with details that will be readily apparent to those of ordinary skill in the art having the benefit of the description herein.